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Measures of model adequacy and model selection in mixed-effects models

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Defense Thèse de doctorat : Univ. Genève, 2016 - GSEM 33 - 2016/09/13
Abstract This thesis contributes to the development of measures of model selection and model adequacy for mixed-effects models. In the context of linear mixed-effects models, we review and compare in a simulation study a large set of measures proposed to evaluate model adequacy or/and to perform model selection. In the more general context of generalized linear mixed-effects models, we develop a measure of both model adequacy and model selection, that we name PRDpen. As a measure of model adequacy, our proposition gives information about the model at hand, as it measures the proportional reduction in deviance due to the model of interest in comparison with a prespecified null model. Furthermore, as a measure of model selection, PRDpen is able to choose the model that best fits the data among a set of alternatives, similarly to the information criteria.
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URN: urn:nbn:ch:unige-905276
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JACOT, Nadège. Measures of model adequacy and model selection in mixed-effects models. Université de Genève. Thèse, 2016. https://archive-ouverte.unige.ch/unige:90527

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Deposited on : 2016-12-19

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